Kerry L. Inder

Plasma membrane nanoswitches generate high-fidelity Ras signal transduction

Ras proteins occupy dynamic plasma membrane nanodomains called nanoclusters. The significance of this spatial organization is unknown. Here we show, using in silico and in vivo analyses of mitogen-activated protein (MAP) kinase signalling, that Ras nanoclusters operate as sensitive switches, converting graded ligand inputs into fixed outputs of activated extracellular signal-regulated kinase (ERK). By generating Ras nanoclusters in direct proportion to ligand input, cells build an analogue–digital–analogue circuit relay that transmits a signal across the plasma membrane with high fidelity. Signal transmission is completely dependent on Ras spatial organization and fails if nanoclustering is abrogated. A requirement for high-fidelity signalling may explain the non-random distribution of other plasma membrane signalling complexes.

Ras membrane orientation and nanodomain localization generate isoform diversity

The structural elements encoding functional diversity among Ras GTPases are poorly defined. The orientation of the G domain of H-ras with respect to the plane of the plasma membrane is recognized by the Ras binding domain of C-Raf, coupling orientation to MAPK activation. We now show that two other proteins, phosphoinositide-3-kinase-α and the structurally unrelated galectin-1, also recognize G-domain orientation. These results rationalize the role of galectin-1 in generating active GTP-H-ras signaling nanoclusters. However, molecular dynamics simulations of K-ras membrane insertion and fluorescence lifetime imaging microscopy (FLIM)-Förster resonance energy transfer (FRET) imaging of the effector interactions of N-Ras, K-Ras, and M-ras suggest that there are two hyperactive, signaling-competent orientations of the Ras G domain. Mutational and functional analyses establish a clear relationship between effector binding and the amphilicities of helix α4 and the C-terminal hypervariable region, thus confirming that these structural elements critically tune the orientation of the Ras G domain. Finally, we show that G-domain orientation and nanoclustering synergize to generate Ras isoform specificity with respect to effector interactions.

Epidermal Growth Factor Receptor Activation Remodels the Plasma Membrane Lipid Environment To Induce Nanocluster Formation

ABSTRACT Signal transduction is regulated by the lateral segregation of proteins into nanodomains on the plasma membrane. However, the molecular mechanisms that regulate the lateral segregation of cell surface receptors, such as receptor tyrosine kinases, upon ligand binding are unresolved. Here we used high-resolution spatial mapping to investigate the plasma membrane nanoscale organization of the epidermal growth factor (EGF) receptor (EGFR). Our data demonstrate that in serum-starved cells, the EGFR exists in preformed, cholesterol-dependent, actin-independent nanoclusters. Following stimulation with EGF, the number and size of EGFR nanoclusters increase in a time-dependent manner. Our data show that the formation of EGFR nanoclusters requires receptor tyrosine kinase activity. Critically, we show for the first time that production of phosphatidic acid by phospholipase D2 (PLD2) is essential for ligand-induced EGFR nanocluster formation. In accordance with its crucial role in regulating EGFR nanocluster formation, we demonstrate that modulating PLD2 activity tunes the degree of EGFR nanocluster formation and mitogen-activated protein kinase signal output. Together, these data show that EGFR activation drives the formation of signaling domains by regulating the production of critical second-messenger lipids and modifying the local membrane lipid environment.

Activation of the MAPK Module from Different Spatial Locations Generates Distinct System Outputs

The Ras/Raf/MEK/ERK (MAPK) pathway directs multiple cell fate decisions within a single cell. How different system outputs are generated is unknown. Here we explore whether activating the MAPK module from different membrane environments can rewire system output. We identify two classes of nanoscale environment within the plasma membrane. The first, which corresponds to nanoclusters occupied by GTP-loaded H-, N- or K-Ras, supports Raf activation and amplifies low Raf kinase input to generate a digital ERKpp output. The second class, which corresponds to nanoclusters occupied by GDP-loaded Ras, cannot activate Raf and therefore does not activate the MAPK module, illustrating how lateral segregation on plasma membrane influences signal output. The MAPK module is activated at the Golgi, but in striking contrast to the plasma membrane, ERKpp output is analog. Different modes of Raf activation precisely correlate with these different ERKpp system outputs. Intriguingly, the Golgi contains two distinct membrane environments that generate ERKpp, but only one is competent to drive PC12 cell differentiation. The MAPK module is not activated from the ER. Taken together these data clearly demonstrate that the different nanoscale environments available to Ras generate distinct circuit configurations for the MAPK module, bestowing cells with a simple mechanism to generate multiple system outputs from a single cascade.

Nucleophosmin and Nucleolin Regulate K-Ras Plasma Membrane Interactions and MAPK Signal Transduction

The spatial organization of Ras proteins into nanoclusters on the inner leaflet of the plasma membrane is essential for high fidelity signaling through the MAPK pathway. Here we identify two selective regulators of K-Ras nanoclustering from a proteomic screen for K-Ras interacting proteins. Nucleophosmin (NPM) and nucleolin are predominantly localized to the nucleolus but also have extranuclear functions. We show that a subset of NPM and nucleolin localizes to the inner leaflet of plasma membrane and forms specific complexes with K-Ras but not other Ras isoforms. Active GTP-loaded and inactive GDP-loaded K-Ras both interact with NPM, although NPM-K-Ras binding is increased by growth factor receptor activation. NPM and nucleolin both stabilize K-Ras levels on the plasma membrane, but NPM concurrently increases the clustered fraction of GTP-K-Ras. The increase in nanoclustered GTP-K-Ras in turn enhances signal gain in the MAPK pathway. In summary these results reveal novel extranucleolar functions for NPM and nucleolin as regulators of K-Ras nanocluster formation and activation of the MAPK pathway. The study also identifies a new class of K-Ras nanocluster regulator that operates independently of the structural scaffold galectin-3.

Expression of PTRF in PC-3 Cells Modulates Cholesterol Dynamics and the Actin Cytoskeleton Impacting Secretion Pathways

Expression of caveolin-1 is up-regulated in prostate cancer metastasis and is associated with aggressive recurrence of the disease. Intriguingly, caveolin-1 is also secreted from prostate cancer cell lines and has been identified in secreted prostasomes. Caveolin-1 is the major structural component of the plasma membrane invaginations called caveolae. Co-expression of the coat protein Polymerase I and transcript release factor (PTRF) is required for caveolae formation. We recently found that expression of caveolin-1 in the aggressive prostate cancer cell line PC-3 is not accompanied by PTRF, leading to noncaveolar caveolin-1 lipid rafts. Moreover, ectopic expression of PTRF in PC-3 cells sequesters caveolin-1 into caveolae. Here we quantitatively analyzed the effect of PTRF expression on the PC-3 proteome using stable isotope labeling by amino acids in culture and subcellular proteomics. We show that PTRF reduced the secretion of a subset of proteins including secreted proteases, cytokines, and growth regulatory proteins, partly via a reduction in prostasome secretion. To determine the cellular mechanism accounting for the observed reduction in secreted proteins we analyzed total membrane and the detergent-resistant membrane fractions. Our data show that PTRF expression selectively impaired the recruitment of actin cytoskeletal proteins to the detergent-resistant membrane, which correlated with altered cholesterol distribution in PC-3 cells expressing PTRF. Consistent with this, modulating cellular cholesterol altered the actin cytoskeleton and protein secretion in PC-3 cells. Intriguingly, several proteins that function in ER to Golgi trafficking were reduced by PTRF expression. Taken together, these results suggest that the noncaveolar caveolin-1 found in prostate cancer cells generates a lipid raft microenvironment that accentuates secretion pathways, possibly at the step of ER sorting/exit. Importantly, these effects could be modulated by PTRF expression.

PTRF/cavin-1 neutralizes non-caveolar caveolin-1 microdomains in prostate cancer

Caveolin-1 has a complex role in prostate cancer and has been suggested to be a potential biomarker and therapeutic target. As mature caveolin-1 resides in caveolae, invaginated lipid raft domains at the plasma membrane, caveolae have been suggested as a tumor-promoting signaling platform in prostate cancer. However, caveola formation requires both caveolin-1 and cavin-1 (also known as PTRF; polymerase I and transcript release factor). Here, we examined the expression of cavin-1 in prostate epithelia and stroma using tissue microarray including normal, non-malignant and malignant prostate tissues. We found that caveolin-1 was induced without the presence of cavin-1 in advanced prostate carcinoma, an expression pattern mirrored in the PC-3 cell line. In contrast, normal prostate epithelia expressed neither caveolin-1 nor cavin-1, while prostate stroma highly expressed both caveolin-1 and cavin-1. Utilizing PC-3 cells as a suitable model for caveolin-1-positive advanced prostate cancer, we found that cavin-1 expression in PC-3 cells inhibits anchorage-independent growth, and reduces in vivo tumor growth and metastasis in an orthotopic prostate cancer xenograft mouse model. The expression of α-smooth muscle actin in stroma along with interleukin-6 (IL-6) in cancer cells was also decreased in tumors of mice bearing PC-3-cavin-1 tumor cells. To determine whether cavin-1 acts by neutralizing caveolin-1, we expressed cavin-1 in caveolin-1-negative prostate cancer LNCaP and 22Rv1 cells. Caveolin-1 but not cavin-1 expression increased anchorage-independent growth in LNCaP and 22Rv1 cells. Cavin-1 co-expression reversed caveolin-1 effects in caveolin-1-positive LNCaP cells. Taken together, these results suggest that caveolin-1 in advanced prostate cancer is present outside of caveolae, because of the lack of cavin-1 expression. Cavin-1 expression attenuates the effects of non-caveolar caveolin-1 microdomains partly via reduced IL-6 microenvironmental function. With circulating caveolin-1 as a potential biomarker for advanced prostate cancer, identification of the molecular pathways affected by cavin-1 could provide novel therapeutic targets.

Cavin-1/PTRF alters prostate cancer cell-derived extracellular vesicle content and internalization to attenuate extracellular vesicle-mediated osteoclastogenesis and osteoblast proliferation

Background Tumour-derived extracellular vesicles (EVs) play a role in tumour progression; however, the spectrum of molecular mechanisms regulating EV secretion and cargo selection remain to be fully elucidated. We have reported that cavin-1 expression in prostate cancer PC3 cells reduced the abundance of a subset of EV proteins, concomitant with reduced xenograft tumour growth and metastasis. Methods We examined the functional outcomes and mechanisms of cavin-1 expression on PC3-derived EVs (PC3-EVs). Results PC3-EVs were internalized by osteoclast precursor RAW264.7 cells and primary human osteoblasts (hOBs) in vitro, stimulating osteoclastogenesis 37-fold and hOB proliferation 1.5-fold, respectively. Strikingly, EVs derived from cavin-1-expressing PC3 cells (cavin-1-PC3-EVs) failed to induce multinucleate osteoblasts or hOB proliferation. Cavin-1 was not detected in EVs, indicating an indirect mechanism of action. EV morphology, size and quantity were also not affected by cavin-1 expression, suggesting that cavin-1 modulated EV cargo recruitment rather than release. While cavin-1-EVs had no osteoclastogenic function, they were internalized by RAW264.7 cells but at a reduced efficiency compared to control EVs. EV surface proteins are required for internalization of PC3-EVs by RAW264.7 cells, as proteinase K treatment abolished uptake of both control and cavin-1-PC3-EVs. Removal of sialic acid modifications by neuraminidase treatment increased the amount of control PC3-EVs internalized by RAW264.7 cells, without affecting cavin-1-PC3-EVs. This suggests that cavin-1 expression altered the glycosylation modifications on PC3-EV surface. Finally, cavin-1 expression did not affect EV in vivo tissue targeting as both control and cavin-1-PC3-EVs were predominantly retained in the lung and bone 24 hours after injection into mice. Discussion Taken together, our results reveal a novel pathway for EV cargo sorting, and highlight the potential of utilizing cavin-1-mediated pathways to attenuate metastatic prostate cancer.

Online quantitative proteomics p-value calculator for permutation-based statistical testing of peptide ratios

The utility of high-throughput quantitative proteomics to identify differentially abundant proteins en-masse relies on suitable and accessible statistical methodology, which remains mostly an unmet need. We present a free web-based tool, called Quantitative Proteomics p-value Calculator (QPPC), designed for accessibility and usability by proteomics scientists and biologists. Being an online tool, there is no requirement for software installation. Furthermore, QPPC accepts generic peptide ratio data generated by any mass spectrometer and database search engine. Importantly, QPPC utilizes the permutation test that we recently found to be superior to other methods for analysis of peptide ratios because it does not assume normal distributions.1 QPPC assists the user in selecting significantly altered proteins based on numerical fold change, or standard deviation from the mean or median, together with the permutation p-value. Output is in the form of comma separated values files, along with graphical visualization using volcano plots and histograms. We evaluate the optimal parameters for use of QPPC, including the permutation level and the effect of outlier and contaminant peptides on p-value variability. The optimal parameters defined are deployed as default for the web-tool at http://qppc.di.uq.edu.au/ .

Ripples in the pond – using a systems approach to decipher the cellular functions of membrane microdomains

Membrane microdomains such as lipid rafts and caveolae regulate a myriad of cellular functions including cell signalling, protein trafficking, cell viability, and cell movement. They have been implicated in diseases such as cancer, diabetes and Alzheimers disease, highlighting the essential role they play in cell processes. Despite much research and debate on the size, composition and dynamics of membrane microdomains, the molecular mechanism(s) of their action remain poorly understood. Most studies have dealt solely with the content and properties of the membrane microdomain as an entity in itself. However, recent work shows that membrane microdomain disruption has wide ranging effects on other subcellular compartments, and the cell as a whole. Hence we propose that a systems approach incorporating many cellular attributes such as subcellular localisation is required in order to understand the global impact of microdomains on cell function. Although analysis of sub-proteome changes already provides additional insight, we further propose biological network analysis of functional proteomics data to capture effects at the systems level. In this review, we highlight the use of protein-protein interactions networks and mixed networks to portray and visualize the relationships between proteins within and between subcellular fractions. Such a systems analysis will be required to improve our understanding of the full cellular function of membrane microdomains.